Assessment Of Degradation Research Articles

Multi-stage exponential model based on subspace clustering distribution for bearing remaining useful life prediction

As one of the key components in rotating machinery, the rolling element bearing has been widely used in actual production, such as wind turbines, vehicles and machine tools. A bearing’s remaining useful life (RUL) is an important indicator for its performance assessment, which is related to maintenance and production safety. To overcome the insensitivity of the conventional health indicator (HI) on bearing degradation assessment, this study proposes a subspace clustering method based on manifold learning to evaluate the evolution of health status, which describes the degenerate distribution via a two-class model and realizes the identification of the degradation of each stage. Motivated by the inconsistent degradation process in the application of actual bearing, this study proposes a multi-stage degradation identification criterion in an adaptive way, which can effectively identify different degradation rates of bearing. Based on the different degradation states, a multi-stage degradation exponential model is established to accurately predict the RUL. The effectiveness of the proposed method is validated through open datasets. The experimental results prove that the proposed method can effectively identify different degradation rates and accurately give the boundary time of the multi-stage degradation. The RUL prediction accuracy is significantly improved compared with traditional HI.

Mapping elemental solutes at sub-picogram levels during aqueous corrosion of Al alloys using diffusive gradients in thin films (DGT) with LA-ICP-MS

A novel approach using diffusive gradients in thin films (DGT) with laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) for two-dimensional mapping of elemental solute release at sub-picogram levels during aqueous corrosion of Al alloys is presented. Evaluation of different DGT gels with mixed micro-sized binding phases (polyacrylamide-Chelex-Metsorb, polyurethane (PU)-Chelex-Metsorb, PU-Chelex-Zr(OH)4) demonstrated the superior performance of PU gels due to their tear-proof handling, low shrinkage, and compliance with green chemistry. DGT devices containing PU-Chelex-Zr(OH)4 gels, which have not been characterized for Al sampling before, showed quantitative uptake of Al, Zn, and Cu solutes over time (t = 4–48 h) with higher Al capacity (ΓDGT = 6.25 µg cm−2) than different gels. Application of PU-Chelex-Zr(OH)4 gels on a high-strength Al-Cu alloy (Al2219) exposed to NaCl (w = 1.5%, pH = 4.5, T = 21 °C) for 15 min in a novel piston-type configuration revealed reproducible patterns of Al and Zn co-solubilization with a spatial expansion ranging between 50 and 1000 µm. This observation, together with complementary solid-state data from secondary electron microscopy with energy-dispersive X-ray spectroscopy, showed the presence of localized pitting corrosion at the material surface. Detection limits for total solute masses of Al, Zn, and Cu were ≤0.72 pg, ≤8.38 pg, and ≤0.12 pg, respectively, for an area of 0.01 mm2, demonstrating the method’s unique capability to localize and quantify corrosion processes at ultra-trace levels and high resolution. Our study advances the assessment of Al alloy degradation in aqueous environments, supporting the design of corrosion-resistant materials for fostering technological safety and sustainability.Graphical

Water-Insoluble, Thermostable, Crosslinked Gelatin Matrix for Soft Tissue Implant Development.

In this present study, the material science background of crosslinked gelatin (GEL) was investigated. The aim was to assess the optimal reaction parameters for the production of a water-insoluble crosslinked gelatin matrix suitable for heat sterilization. Matrices were subjected to enzymatic degradation assessments, and their ability to withstand heat sterilization was evaluated. The impact of different crosslinkers on matrix properties was analyzed. It was found that matrices crosslinked with butanediol diglycidyl ether (BDDE) and poly(ethylene glycol) diglycidyl ether (PEGDE) were resistant to enzymatic degradation and heat sterilization. Additionally, at 1 v/v % crosslinker concentration, the crosslinked weight was lower than the starting weight, suggesting simultaneous degradation and crosslinking. The crosslinked weight and swelling ratio were optimal in the case of the matrices that were crosslinked with 3% and 5% v/v BDDE and PEGDE. FTIR analysis confirmed crosslinking, and the reduction of free primary amino groups indicated effective crosslinking even at a 1% v/v crosslinker concentration. Moreover, stress-strain and compression characteristics of the 5% v/v BDDE crosslinked matrix were comparable to native gelatin. Based on material science measurements, the crosslinked matrices may be promising candidates for scaffold development, including properties such as resistance to enzymatic degradation and heat sterilization.

Residue Degradation and Risk Assessment of Difenoconazole and Its Metabolite during Tea Growing, Processing and Brewing by Ultra-Performance Liquid Chromatography-Tandem Mass Spectrometry Determination.

Residue dissipation and risk assessment of difenoconazole and its metabolite difenoconazole-alcohol during tea growing, processing, and brewing was first investigated by ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS). The limits of quantification for both difenoconazole and difenoconazole-alcohol were 0.001 mg/kg in fresh tea leaves and tea, and 0.0002 mg/L in tea infusion. In field trials, the dissipation half-lives of difenoconazole in fresh tea leaves was 1.77 days. After spraying, the residues of difenoconazole-alcohol increased and then gradually dissipated like difenoconazole. After 14 days, the dissipation rates of difenoconazole and difenoconazole-alcohol reached 99%. When fresh tea leaves were harvested on different days, the total processing factors (PFs) of difenoconazole and difenoconazole-alcohol for green tea were 0.86-1.05 and 0.78-0.85, respectively, while the total PFs for black tea were 0.83-1.13 and 0.82-1.66, respectively. Metabolism of difenoconazole was accelerated during tea processing. When brewing black tea, the leaching rates (LRs) of difenoconazole and difenoconazole-alcohol were 8.4-17.9% and 31.8-38.9%, respectively, while when brewing green tea, the LRs were 15.4-23.5% and 30.4-50.6%, respectively. The LRs of difenoconazole and difenoconazole-alcohol in black tea were higher than those in green tea. The potential threat to human health for dietary intake of difenoconazole and difenoconazole-alcohol residues from tea consumption is negligible. However, the dietary risk of difenoconazole in fruits and vegetables that are essential for daily diets is concerning, with a risk probability of 158%.

Mechanical analysis and biodegradation of oxides-based magneto-responsive shape memory polymers for material extrusion 3D printing of biomedical scaffolds

The development of advanced smart polymers, characterized by superior strength, exceptional quality, biodegradability, and lightweight structures, stands as a paramount concern in the context of biomedical implant materials. Aiming at the requirements of a tracheal scaffold, this research focuses on developing magnetic shape memory polymers using solvent evaporation method and characterizing their morphology, viscoelastic, thermodynamic, mechanical and shape memory properties. Furthermore, an assessment of degradation is conducted, along with an evaluation of tensile strength both pre- and post-degradation. The findings reveal that the dispersion of Fe3O4 nanoparticles exhibits homogeneity at a 15 wt% concentration but tends to aggregate at high proportions. The glass transition temperature increases with the addition of Fe3O4, while less than 10% ratio of the Fe3O4 cannot activate the magnetic actuation. Notably, the tensile and elastic modulus for the 15 wt% Fe3O4 composition measure at 59.70 MPa and 24.68 MPa, respectively, and exhibit a diminishing trend with higher nanofiller content. Subsequently, it demonstrates favorable thermal and magnetic shape memory behavior, yielding reasonable shape recovery ratios. Over a degradation period of 120 days, a reduction in average weight loss was observed for 15 wt% concentration, while higher for higher concentrations due to their non-uniform dispersion. Post-degradation, the tensile strength experiences a decline with proportional reduction of 41.15%, 37.61%, 47.13%, 42.46%, and 54.77%, respectively. Based on the finite element analysis, the multi-objective optimization of the structural parameters of the tracheal stent was carried out, and manufactured by material extrusion 3D printing. Finally, the stability, flexibility and compression properties of the scaffold were tested by relevant experimental tests, which ensured the suitability (foldability) of scaffolds. In conclusion, the developed magnetic shape memory polymers showed promising potential for biomedical scaffolds preparation.

Quantitative Soil Quality Assessment by Using Visual Soil-Field Assessment Tools (VS-FAST)

Unplanned land use reflects the changes from agricultural to urbanization and decreasing of green spaces in cities and agricultural lands surrounding cities. The Soil Adjusted Vegetation Index (SAVI), Dry Bare - Soil Index (DBSI) and Normalized Difference Built-up Index (NDBI) indices were derived to evaluate the rate of the land use/cover changes due to uncontrolled urban sprawl for the years 2001 and 2020. Field indicators were also used to assess soil properties’ degradation by using Land Degradation Assessment in Drylands (LADA) under the FAO Global Environment Facility (GEF) project. A set of 30 soil samples were randomly collected from two locations: unplanned built-up and vegetated sites in Babil Governorate, Iraq. The results showed that soil texture and salinity were the most varied indicators. The poorer areas (unplanned urban areas) were low and assessed as poor quality, while the vegetated site was assessed as moderate quality with high total score values. The findings from spectral indices show a significant rise in the built-up land use/cover category, expanding from 10.367 square kilometres in 2001 to 50.883 square kilometres in 2020. In contrast, the areas of bare-soils and vegetated decreased from 29.29 and 35.474 square kilometres in 2001 to 12.511 and 19.601 square kilometres in 2020, respectively. Various analytical techniques proved instrumental in distinguishing the different land use/cover categories in this research.

Random Forest-Based Assessment of Mangrove Degradation Utilizing NDVI Feature Extraction in Spatio-Temporal Analysis

Mangrove ecosystems, vital for coastal biodiversity and protection, confront escalating degradation from human and natural influences. Addressing the imperative for precise degradation assessment, this study introduces a Random Forest-based technique, utilizing NDVI (Normalized Difference Vegetation Index) feature extraction within a spatio-temporal framework. The principal aim is to establish a robust approach for evaluating mangrove degradation and land cover shifts. This involves extracting NDVI values from satellite images to monitor vegetation health and changes chronologically. Leveraging the Random Forest algorithm, acknowledged for managing intricate relationships and classifications, further enhances the methodology.By situating the approach spatio-temporally, degradation patterns and alterations in mangrove distribution are traced over time. The temporal progression of the study area is considered, affording a thorough degradation analysis. Outcomes affirm the method's efficacy, evidenced by a Cohen's Kappa Score of 0.96 denoting substantial agreement between predictions and observations. Remarkably high scores across accuracy, precision, recall, and F1-score (all at 0.97) underscore the model's precision in classifying mangrove degradation levels. The amalgamation of the Random Forest-based approach and NDVI feature extraction emerges as a valuable instrument for precise mangrove degradation assessment. The spatio-temporal analysis augments comprehension of degradation dynamics, pivotal for proficient mangrove management and conservation strategies.

Green Synthesis of Metal-Doped ZnO Nanoparticles Using Bauhinia racemosa Lam. Extract and Evaluation of Their Photocatalysis and Biomedical Applications.

A fascinating problem in the fields of nanoscience and nanobiotechnology has recently emerged, and to tackle this, the production of metal oxide nanoparticles using plant extracts offers numerous benefits over traditional physicochemical methods. In the present investigation, ZnO nanoparticles were fabricated from Bauhinia racemosa Lam. (BR) leaves extract with various transition metal (TM) dopants (Ni, Mn, and Co). Plant leaves extract containing metal nitrate solutions were utilized as a precursor to synthesize the pristine and TM-doped ZnO nanoparticles. Structural, functional, optical, and surface properties of the fabricated samples were studied by using physicochemical and photoelectrochemical measurements. The organic pollutants tetracycline (TC), ampicillin (AMP), and amoxicillin (AMX) were used in the photocatalytic degradation assessment of the fabricated samples. Through X-ray diffraction (XRD) and transmission electron microscopy (TEM) investigation, the fabricated nanoparticles wurtzite crystal structure was verified. Moreover, Fourier transform infrared (FT-IR) analysis verified the existence of functional groups in the fabricated nanoparticles. The migration of electrons from the deep donor level and zinc interstitial to the Zn-defect and O-defect is related to the emission peaks seen at 468, 480, 534, and 450 nm in photoluminescence (PL) spectra. Co-ZnO nanoparticles demonstrated potent and excellent photocatalytic degradation performance for TC (91.09%), AMP (87.97%), and AMX (92.42%) antibiotics within 210, 180, and 150 min of visible light irradiation. Co-ZnO nanoparticles also demonstrated strong antimicrobial performance against Escherichia coli, Staphylococcus aureus, Klebsiella pneumoniae, Aspergillus flavus, Aspergillus niger, and Bacillus subtilis. Further investigation of in vitro cytotoxic potential against the A549 cell line (IC50 = 24 ± 0.5 μg/mL) utilizing MTT assay and the free radical scavenging performance of Co-ZnO nanoparticles estimated by DPPH assay utilizing l-ascorbic acid as a reference was also performed. Anti-inflammatory potential is also reviewed by comparing it with the standard drug Diclofenac, and the maximum activity was obtained for Ni-ZnO nanoparticles (IC50 = 72.4 μg/mL).

Fractographic justification of fracture resistance loss in steel elements of overloaded machinery metal constructions

The problem related to the loss of resistance to brittle fracture in steel elements of the metal structure of loading equipment has been investigated. A fracto- graphic analysis was conducted at macro and micro levels on samples taken from two sections of the crane that underwent testing to determine their impact toughness. The selected samples covered the least and most loaded areas of the crane's metal structure to reflect the minimum and maximum levels of operational steel degradation. The assessment of metal degradation was carried out based on its resistance to brittle fracture. A correlation was established between the nature of the fracture, energy absorption, and indicators of resistance to brittle fracture. Special attention was given to the location of delamination along the direction of rolling during macro and microfracto- graphic studies. Macrofractographic analysis confirmed the general tendency of the metal to delaminate, especially along the fibers of the texture. This tendency varied for different sections of the crane's metal structure and depended on the level of operational stresses in the structural elements. It was found that longitudinal samples exhibited fractographic signs of delamination in the form of secondary cracks perpendicular to the fracture plane. The macrofracture of a sample from a loaded area revealed a significant amount of delamination, indicating their role in the propagation of fractures during impact tests. These results allow establishing a connection between the material's structure, its mechanical properties, and operational degra-dation, which is crucial for improving the reliability and safety of crane metal structures

Abstract 2323: Deciphering RNA degradation: Insights from a comparative analysis of paired fresh frozen/FFPE total RNA-seq

Abstract Background: Fresh frozen (FF) and formalin-fixed paraffin-embedded (FFPE) samples are primary resources for archival tissues in cancer studies. Despite the advantages of easy storage and cost-effectiveness, FFPE samples have the disadvantage of inevitable chemical-induced RNA degradation. Although, in mRNA-seq data, the 3' bias due to the characteristics of the mRNA-seq platform allows the measure of RNA degradation levels, for total RNA-seq and FFPE samples, there is still no clear measure for RNA degradation. Methods: Our study, utilizing The Cancer Genome Atlas (TCGA) pilot data comprised of 26 paired samples of fresh frozen mRNA-seq [FFM], fresh frozen total RNA-seq [FFT], and FFPE total RNA-seq [PET], investigated RNA degradation patterns in FFPE samples. Upon investigating the read coverage of transcripts in FFPE data, we observed increased noise parameters in selected samples compared to others, suggesting a method for assessment of RNA degradation in FFPE. To measure these noise patterns, we developed a method called windowCV (wCV) utilizing coefficient of variance (CV) along the transcript length. Also, based on reports that membrane-surrounded RNA such as lncRNA and mitochondrial RNA (mtRNA) might be less affected by formalin fixation, we developed the simple measure dividing expression value of other proteins with certain lncRNA or mtRNA inferring the degree of RNA degradation. Results: We first compared the shape of transcript read coverage from 3 different RNA-seq data and observed 3’bias pattern in FFM which was not observed in FFT and PET. For FFT and PET, we applied wCV and executed hierarchical clustering. We observed that a subset of samples and genes were clustered by high wCV value suggesting notable RNA degradation. To support the hypothesis of RNA degradation, we utilized Trimmed Mean of M values (TMM) expression ratio of paired FFT and PET to determine which samples and genes were associated with underestimation of expression in PET. Interestingly, we observed that PET/FFT TMM ratio showed negative correlation with wCV. Additionally, when we investigated hierarchical clustering result of PET/FFT TMM ratio, we found that lncRNA and mtRNA were less affected by FFPE. We then calculated expression ratio between membrane-surrounded RNA and a set of protein coding genes largely affected by FFPE. As a result, we found that this ratio positively correlated with paired PET/FFT TMM ratio. We conclude that this simple measurement can provide information of FFPE induced underestimated expression with limited transcriptome data as well as RNA degradation. Conclusion: Our method can provide gene-level CV while avoiding false positive variance signal originating from transcript model and simple way to detect the degree of RNA degradation across FFPE samples. Citation Format: Wonyoung Choi, Miyeon Yeon, Hyo Young Choi, David Neil Hayes. Deciphering RNA degradation: Insights from a comparative analysis of paired fresh frozen/FFPE total RNA-seq [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2323.

Degradation assessment of a single junction InP solar cell under 1 MeV electron irradiation effect

Degradation assessment of a single junction InP solar cell under 1 MeV electron irradiation effect

Application of machine learning in ultrasonic diagnostics for prismatic lithium-ion battery degradation evaluation

Lithium-ion batteries are essential for electrochemical energy storage, yet they undergo progressive aging during operational lifespan. Consequently, precise estimation of their state of health (SOH) is crucial for effective and safe operation of energy storage systems. This paper investigates the viability of ultrasound-based methods for assessing the SOH of prismatic lithium-ion batteries. In the experimental framework, a designated prismatic lithium-ion battery was subjected to numerous charging and discharging cycles using a battery cycling system. Subsequently, ultrasonic detection experiments were conducted to record the waveforms of the transmitted and received signals. These signals were then processed through wavelet transforms to extract signal amplitude and time-of-flight data. To analyse these data, we applied four algorithms: linear regression, support vector machines, Gaussian process regression, and neural networks. The predictive performance of each algorithm was evaluated through extensive experimentation and analysis. The combination of ultrasonic signals with computational models has emerged as a robust technique for precise battery degradation assessment, suggesting its potential as a standard in battery health evaluation methods.

Methods for economic assessment of forest resource degradation: A systematic review

Forest degradation is one of the challenges facing the planet today. Several methods have been used to measure forest degradation, including spatiotemporal model analysis, satellite analysis, remote sensing, time series data, geospatial techniques, and most recently aerial drone imagery. However, few studies have used economic valuation methods to assess forest degradation. Therefore, this research aimed to identify the methods used the economic assessment of forest degradation. This systematic review was carried out using PRISMA guidelines. Research articles on the economic valuation of forest resource loss, published from 2015 to 2022, were electronically collected from three databases. Three independent reviewers, with the third acting as referee, inventoried articles, extracted data, and assessed the risk of bias in the articles included in the study. A total of 10,095 articles were identified, including one article from the grey literature. Only five articles met the eligibility criteria. A qualitative content analysis was performed on the extracted data. The selected articles used various methods. However, only a few articles used the contingent valuation method, even though this is indicated for estimating the highest economic value of forests. Based on forest functions, the articles evaluated erosion due to the absence of trees, wood loss, recreation areas and externalities due to forest loss, air quality, water regulation, food supply, and wildlife. The main limitation of this review was the small number of studies included, which may have affected the findings. The study protocol is registered in PROSPERO under the number CRD42021223242

A novel performance degradation assessment method for rotating machinery based on the fault information and the dynamic simulation

The performance degradation assessment (PDA) of key components such as gears and rolling bearings is the core technology of prognostics and health management for rotating machinery. Most existing PDA methods may have two deficiencies: (1) the assessment indicator constructed does not consider capturing fault characteristics directly; (2) feature selection is generally based on the measured data of different fault levels, which is difficult to obtain in actual processes; moreover, the selection results lack universality and are difficult to extend to other equipment. To address these issues, this paper proposes a novel PDA method based on fault information and dynamic simulation. First, anomaly detection is performed using four well-known indicators in combination with Mahalanobis distance. Secondly, fault identification is performed using envelope spectrum analysis on anomaly signals to determine the fault type, e.g. gear fault or outer race fault. Thirdly, based on the fault type information, the candidate feature set including fault-domain indicators is selected based on the established dynamic simulation signals to obtain a preliminary assessment vector for the first stage. The stability of the fault domain indicators which capture fault characteristics directly is tested through actual measured normal data. It is used as the second stage of selecting to obtain the assessment vector. Finally, the PDA indicator is calculated based on the assessment vector and Mahalanobis distance. Four experiment case studies demonstrate the proposed PDA method can effectively isolate faults with different defect sizes as well as track the whole performance degradation. The above analysis indicates that the proposed PDA method is expected to be used for the actual rotating machinery.

Integrated Universal Soil Loss Equation (USLE) and Geospatial Approach to Assess Soil Erosion in Machhu Sub-watershed, Morbi, India

Abstract Soil erosion is a severe and rapidly rising issue in many parts of the world due to human activities such as farming practices, land excavation for development and deforestation. Moreover, it can negatively impact water availability, agricultural growth, and ultimately, countries’ long-term economy. A quantitative and consistent land degradation assessment is vital for proper planning of soil conservation activities in a catchment or watershed. The Universal Soil Loss Equation (USLE) model is applied in this study to address the issue of soil erosion in the Machhu-sub watershed (24769.63 ha), located in Saurashtra, India. The landscape feature of the study area includes basalt type rock and water body. In this USLE model study we have used input parameters such as rainfall erosivity (R), soil erosivity (K), cover management (C), slope length and steepness (LS), and conservation practice (P) integrated with Geographical Information System (GIS) to analyze and obtain the estimated annual soil loss. Results indicated that the overall soil loss in the study area can be classified into five categories: Very Low (0-1), Low (1-3), Low moderate (3-5), Moderate (5-10), and High ( >10 tons/ha/year). The finding includes the overall soil potential loss of the Machhu sub-watershed is 14.90 tons/ha/year. Furthermore, 60.86 % of the agricultural area is affected by soil erosion. Therefore, the necessary soil conservation methods can be planned in the Machu-sub watershed area based on the USLE analysis. These findings may assist researchers, scientists, and policymakers in building a concrete strategy for sustainable development of not only study area but other catchments also.

Assessment of articular cartilage degradation in response to an impact injury using µMRI

ABSTRACT Purpose Degradation of articular cartilage (AC) due to injury to the knee joint may initiate post-traumatic osteoarthritis (PTOA). Failure to diagnose the onset of the disease at an early stage makes the cure ineffective for PTOA. This study investigated the consequences of a mechanical injury to the knee in a rabbit model using microscopic magnetic resonance imaging (µMRI) at high resolution. Materials and methods A mechanical injury was induced to the knee joints of 12 rabbits. Cartilage blocks were extracted from the non-impacted and impacted knee joints after 2 and 14 weeks post-impact. The specimens were studied using µMRI T2 relaxation and inductively coupled plasma analysis to determine the early degradation of the articular cartilage. Results The data established a connection between T2 relaxation time and the early progression of knee PTOA after an impact injury. T2 values were found to be higher in the impacted cartilage at both 2 and 14 weeks, in particular, T2–55° values in the impacted samples displayed a significant rise of 6.93% after 2 weeks and 20.02% after 14 weeks. Lower glycosaminoglycan measurement and higher water content in the impacted cartilage confirmed the µMRI results. Conclusions This µMRI T2 study was able to detect cartilage damage in the impacted knees. In addition, greater degradation in the affected knees at 14 weeks than at 2 weeks indicated the progressive nature of cartilage deterioration over time. The µMRI results were in accord with the biochemical analysis, indicating the detection of early structural damage in the cartilage.

Assessment of plastic degradation by indigenous bacteria from waste disposal sites

The present study focuses on the isolation of bacterial pathogens from waste disposal sites, and examination of their efficiencies for degrading various plastics. Seven bacterial isolates such as E. coli, Corynebacterium spp., Micrococcus spp., Azotobacter spp., Pseudomonas spp., Staphylococcus spp., and Bacillus spp. were identified. Bacillus spp. exhibited the highest percentage reduction in black plastic weight (47.46 %), while Corynebacterium spp., and E. coli achieved a maximum reduction of 45.76 and 46.42 % for pink plastic respectively. Pseudomonas spp. and Micrococcus spp. demonstrated notable reductions of 46.43 % and 56.60 % in white and Canteen Stores Department (CSD) biodegradable plastics, respectively. Optical density (OD) measurements revealed that bacterial isolates achieved maximum OD values with CSD plastics, emphasizing their proficiency in plastic degradation. Fourier Transform Infrared Spectroscopy (FTIR) confirmed the degradation process, with a decrease in the peak value from 2916 to 2914 cm⁻1 for pink plastic, signifying alkane, and alkene presence. Three new peaks at 1398, 1371, and 1361 cm⁻1 in the FTIR spectrum of CSD plastic indicated presence of alcohol. Scanning Electron Microscopic (SEM) micrographs illustrated bacterial colonization, cracks, and spots on plastic surfaces, while X-ray Diffraction (XRD) spectra showed peaks at 4.083, 3.705, 3.020, and 1.909, suggesting plastic degradation. In conclusion, soil of waste disposal site harbored diverse microbial species, and have highlighted their effectiveness in mitigating environmental pollution by degrading hazardous plastic waste.

Antimicrobials in Eisenia fetida earthworms: A comprehensive study from method development to the assessment of uptake and degradation

In this work, an accurate analytical method was developed for the simultaneous analysis of twenty-seven antimicrobials (AMs) in earthworms using liquid chromatography coupled to a triple quadrupole mass spectrometry detector (UHPLC-MS/MS). Adequate apparent recoveries (80–120 %) and limits of quantification (LOQ) (1 μg·kg−1 - 10 μg·kg−1) were obtained, with the exception of norfloxacin (34 μg·kg−1). The method was applied to evaluate the accumulation of sulfamethazine (SMZ) and tetracycline (TC) in earthworms after performing OECD-207 toxicity test, in which Eisenia fetida (E. fetida) organisms were exposed to soils spiked with 10 mg·kg−1, 100 mg·kg−1 or 1000 mg·kg−1 of SMZ and TC, individually. The results confirmed the bioaccumulation of both AMs in the organisms, showing a greater tendency to accumulate SMZ since higher bioconcentration factor values were obtained for this compound at the exposure concentrations tested. In addition, the degradation of both AMs in both matrices, soils and earthworms was studied using liquid chromatography coupled to a q-Orbitrap high resolution mass spectrometry detector. Thirteen transformation products (TPs) were successfully identified, eight of them being identified for the first time in soil/earthworm (such as 4-Amino-3-chloro-n-(4,6-dimethylpyrimidin-2-yl)benzenesulfonamide or 4-(dimethylamino)-1,11,12a-trihydroxy-6,6-dimethyl-3,7,10,12-tetraoxo-3,4,4a,5,5a,6,7,10,12,12a-decahydrotetracene-2-carboxamide, among others) and their formation/degradation trend over time was also studied. Regarding the biological effects, only SMZ caused changes in earthworm growth, evidenced by weight loss in earthworms exposed to concentrations of 100 mg·kg−1 and 1000 mg·kg−1. Riboflavin decreased at all concentrations of SMZ, as well as at the highest concentration of TC. This indicates that these antibiotics can potentially alter the immune system of E. fetida. This research represents a significant advance in improving our knowledge about the contamination of soil by AM over time. It investigates the various ways in which earthworms are exposed to AMs, either by skin contact or ingestion. Furthermore, it explores how these substances accumulate in earthworms, the processes by which earthworms break them down or metabolise them, as well as the resulting TPs. Finally, it examines the potential effects of these substances on the environment.

Ecosystem richness degradation assessment from elevated hydro-chemical properties of Chilka Lake, India

ABSTRACT A hydrogeochemical analysis of Chilka Lake Ramsar sites has been conducted to measure the surface water quality status and ecological suitability for aquatic habitats. Degree of contamination, water quality index and ecological risk index field-based techniques were employed to analyse the hydro-chemical properties using 48 water samples from across the entire Ramsar region. Among them, 14 predominant factors were identified. The Ramsar area is categorized into five water quality and ecological risk zones with reference to Indian and World Health Organization water quality standards. This field-based study reveals that in the southern, southeastern, and central parts, about 9.89% and 16.12% of areas experienced very poor and poor water quality standards, respectively. Thus, this research work will help government authorities and policymakers formulate appropriate strategies and regulations for controlling and reducing the contamination levels in the Chilka Ramsar region.

Scalable phylogenetic Gaussian process models improve the detectability of environmental signals on local extinctions for many Red List species

Abstract Conservation biologists have a daunting task of understanding the causes of species decline associated with anthropogenic factors and predicting the extinction risk of a growing number of endangered species. By reducing variances of estimates with information on closely related species, phylogenetic information among species can bridge gaps in information on species with small range sizes when modelling large numbers of endangered species. However, modelling many species with the Gaussian process (GP), which underlies the evolutionary process of phylogenetic random effects, remains a challenge owing to the computational burden in estimating the large variance–covariance matrix. Here, we applied a phylogenetic generalised mixed model with random slopes and random intercepts to 1010 endangered vascular plant taxa in Japan following phylogenetic GPs implemented by nearest neighbour GP (NNGP) approximation. NNGP enables flexibility in changing the proximity on the phylogenetic tree of species from which information is borrowed to reduce the variances of estimates with a realistic computational burden. We evaluated the effectiveness of phylogenetic models by comparing the predictive performance and descriptive power of phylogenetic and non‐phylogenetic models and identified the anthropogenic factors contributing to the decline of each of the studied endangered species. We found that the model with phylogenetic information had better prediction performance than the model without phylogenetic information. The results showed that across all explanatory variables, the phylogenetic model could detect interspecific differences in response to environmental factors in a number of species more clearly. Combined with the phylogenetic signal results, we could also detect a phylogenetic bias in the species that could benefit from the positive effects of protected areas but reduce the local extinctions of 95% of all studied taxa. In conclusion, our model, considering phylogenetic information with NNGP, allows the elucidation of factors causing the decline of many endangered species. In future analyses, the estimation of extinction probability linked to environmental change might be applied to future climate–land use scenarios, advancing the comprehensive assessment of biodiversity degradation and threats to species at multiple scales.